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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases |
| Topic 2: Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration - Understand agent use cases and types |
| Topic 3: Implement computer vision solutions | 10-15% | - Build and deploy custom vision models - Integrate vision capabilities into applications - Analyze images and detect objects/features - Extract text and handwriting from images - Process and index video content |
| Topic 4: Plan and manage an Azure AI solution | 20-25% | - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Create and configure Azure AI resources - Select suitable AI models - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles |
| Topic 5: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models |
| Topic 6: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Apply prompt engineering and fine-tuning - Deploy and manage generative models - Implement model monitoring and feedback |
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NEW QUESTION # 97
What should you use to build a Microsoft Power Bi paginated report?
Answer: D
Explanation:
Paginated reports are designed for printing or PDF generation, with table-style reports that span multiple pages.
These are built using Power BI Report Builder , a standalone tool.
B). Charticulator is for creating custom visuals, not paginated reports.
C). Power BI Desktop builds interactive reports, dashboards, and data models, not paginated reports.
D). Power BI Service is for publishing, sharing, and consuming reports, but not building paginated reports.
Reference: Paginated reports in Power BI
NEW QUESTION # 98
You run the following command.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Answer:
Explanation:
Explanation
Text Description automatically generated
Box 1: Yes
http://localhost:5000/status
Also requested with GET, this verifies if the api-key used to start the container is valid without causing an endpoint query.
Box 2: Yes
The command saves container and LUIS logs to output mount at C:\output, located on container host Box 3: Yes
http://localhost:5000/swagger
The container provides a full set of documentation for the endpoints and a Try it out feature. With this feature, you can enter your settings into a web-based HTML form and make the query without having to write any code. After the query returns, an example CURL command is provided to demonstrate the HTTP headers and body format that's required.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto
NEW QUESTION # 99
Case Study 2 - Contoso, Ltd.
General Overview
Contoso, Ltd. is an international accounting company that has offices in France. Portugal, and the United Kingdom. Contoso has a professional services department that contains the roles shown in the following table.
Infrastructure
Contoso has the following subscriptions:
- Azure
- Microsoft 365
- Microsoft Dynamics 365
Azure Active (Azure AD) Directory
Contoso has Azure Active Directory groups for securing role-based access. The company uses the following group naming conventions:
- ICountryJ-[Levell-[Role]
- [Level]-[Role]
Intellectual Property
Contoso has the intellectual property shown in the following table.
Text-based content is provided only in one language and is not translated.
Planned Projects
Contoso plans to develop the following:
- A document processing workflow to extract information automatically from PDFs and images of financial documents
- A customer-support chatbot that will answer questions by using FAQs
- A searchable knowledgebase of all the intellectual property
Technical Requirements
Contoso identifies the following technical requirements:
- All content must be approved before being published.
- All planned projects must support English, French, and Portuguese.
- All content must be secured by using role-based access control (RBAC).
- RBAC role assignments must use the principle of least privilege.
- RBAC roles must be assigned only to Azure Active Directory groups.
- Al solution responses must have a confidence score that is equal to or greater than 70 percent.
- When the response confidence score of an Al response is lower than 70 percent, the response must be improved by human input.
Chatbot Requirements
Contoso identifies the following requirements for the chatbot:
- Provide customers with answers to the FAQs.
- Ensure that the customers can chat to a customer service agent.
- Ensure that the members of a group named Management-Accountants can approve the FAQs.
- Ensure that the members of a group named Consultant-Accountants can create and amend the FAQs.
- Ensure that the members of a group named the Agent-CustomerServices can browse the FAQs.
- Ensure that access to the customer service agents is managed by using Omnichannel for Customer Service.
- When the response confidence score is low.
- Ensure that the chatbot can provide other response options to the customers.
Document Processing Requirements
Contoso identifies the following requirements for document processing:
- The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
- The document processing solution must be able to extract tables and text from the financial documents.
- The document processing solution must be able to extract information from receipt images.
- Members of a group named Management-Bookkeeper must define how to extract tables from the financial documents.
- Members of a group named Consultant-Bookkeeper must be able to process the financial documents.
Knowledgebase Requirements
Contoso identifies the following requirements for the knowledgebase:
- Supports searches for equivalent terms
- Can transcribe jargon with high accuracy
- Can search content in different formats, including video
- Provides relevant links to external resources for further research
You need to develop an extract solution for the receipt images. The solution must meet the document processing requirements and the technical requirements.
You upload the receipt images to the Azure AI Document Intelligence API for analysis, and the API returns the following JSON.
Which expression should you use to trigger a manual review of the extracted information by a member of the Consultant-Bookkeeper group?
Answer: C
Explanation:
Need to specify the field name, and then use < 0.7 to handle trigger if confidence score is less than 70%.
Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/api-v2-0/reference- sdk-api-v2-0
NEW QUESTION # 100
Match the Azure Cosmos DB APIs to the appropriate data structures.
To answer, drag the appropriate API from the column on the left to its data structure on the right. Each API may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
NEW QUESTION # 101
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a chatbot that uses question answering in Azure Cognitive Service for Language Users report that the responses of the chatbot lack formality when answering spurious questions You need to ensure that the chatbot provides formal responses to spurious questions.
Solution: From Language Studio, you change the chitchat source to qna_chitchat_professional.tsv. and then retrain and republish the model.
Does this meet the goal?
Answer: A
Explanation:
* The chatbot uses Question Answering in Azure Cognitive Service for Language.
* Users report that the chatbot's responses to spurious questions (such as jokes, casual chitchat, or off- topic queries) are not formal enough.
Comprehensive Detailed ExplanationIn Question Answering projects, you can add chitchat sources provided by Microsoft to handle small talk. These sources include:
* qna_chitchat_friendly.tsv # Informal/friendly responses.
* qna_chitchat_professional.tsv # Formal/professional responses.
* qna_chitchat_witty.tsv # Humorous/witty responses.
By changing the chitchat source to qna_chitchat_professional.tsv, then retraining and republishing, the bot will provide formal responses to spurious questions.
Therefore, this solution meets the goal.
The answer: A. Yes
* Add chit-chat to a Question Answering project
* Chit-chat personality types (friendly, professional, witty)
Microsoft References
NEW QUESTION # 102
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